Top Senior Analytics Jobs in NYC, NY

Direct advanced analytics for a marketing agency, leading a team that develops statistical models, marketing mix models, attribution algorithms, campaign tests, and ROI analyses. Manage client engagements, mentor analysts, improve analytical methodologies, productionize models, and collaborate with business intelligence and data engineering teams. Translate complex technical findings into actionable business recommendations while supporting media optimization and marketing effectiveness initiatives.

Leads College Board’s Operations analytics strategy and team, developing forecasting, predictive modeling, optimization, cost assessment, and decision-support capabilities. Partners with senior leaders across Operations, Product, Program, Technology, and Finance to improve execution, customer experience, efficiency, and cost savings. Responsibilities include setting technical direction, embedding analytics into operational decisions, presenting insights, hiring and coaching analytics staff, and building future AI and data-infrastructure capabilities.

Leads internal data analysis projects, identifies business opportunities and risks, delivers strategic insights to leadership, manages junior analysts, develops dashboards, and improves data quality across company platforms. The role requires translating quantitative findings for nontechnical audiences and applying healthcare or pharmaceutical dataset experience to strategic decision-making.

Use data analytics to identify and reduce operational risk across EP & TBM. Analyze large datasets, perform root cause analysis, recommend scalable process improvements, build dashboards and visualizations, measure initiative effectiveness, automate reporting, and partner with engineering, product, and risk teams to prioritize and implement risk reduction.

Own enterprise analytics audits, implementations, data quality, attribution, segmentation, SQL analysis, BI dashboards, experimentation measurement, and client reporting. Serve as the senior analytics partner for major accounts, present insights to executives, train client and internal teams, and help define analytics and experimentation services. The role requires hands-on Adobe expertise, autonomous prioritization, technical collaboration, and the ability to connect organic and AI search performance to pipeline and revenue.

Provide quantitative analytics and reporting for private credit portfolios (Direct Lending, Asset-Based Finance, Structured Credit). Build and automate models, dashboards, and data workflows; validate and reconcile investment data; support underwriting, portfolio monitoring, risk oversight, and senior reporting; collaborate with investment, risk, finance, operations, and technology teams.

Lead people-analytics strategy for Talent Acquisition and Talent Development. Drive end-to-end analysis of complex workforce problems, deliver evidence-based recommendations to senior leaders, ensure data governance and quality, coach junior analysts, build metrics frameworks, and conduct benchmarking and external research to inform workforce strategy.

The Lead Risk Analytics Data Scientist will develop risk pricing, design data models, automate workflows, and communicate insights to leadership. Responsibilities include owning the risk narrative, building analytics foundations, and utilizing AI to enhance efficiency.

The Staff Data Scientist will work with product teams to analyze data, identify improvement opportunities, design experiments, and create reporting dashboards to enhance contract management workflows.

The Senior Data Scientist will design and deploy time-series forecasting models, collaborate with stakeholders, and operationalize models in cloud environments, focusing on demand planning across various industries.

Lead market access deal analytics by developing data-driven solutions for payer strategy and reimbursement optimization, conducting claims data analyses, and integrating analytics into pricing strategies. Required to manage healthcare datasets and develop predictive models.

Lead implementations and ongoing analytics consulting for community health centers: extract, clean, and analyze EHR data (heavy SQL), build reports and visualizations, manage projects and stakeholders, train client data teams, and inform product improvements based on customer feedback and domain expertise.